Processing Big Data for Emergency Management

Processing Big Data for Emergency Management

Rajendra Akerkar (Western Norway Research Institute, Norway)
DOI: 10.4018/978-1-5225-6195-8.ch045
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Emergencies are typically complex problems with serious consequences that must be solved in a limited amount of time to reduce any possible damage. Big data analysis leads to more assured decision making and better decisions can mean greater operational efficiencies, cost reductions and reduced risk. In this chapter, we discuss some issues on tackling emergency situation from the perspective of big data processing and management, including our approach for processing social media content. Communications during emergencies are so plentiful that it is necessary to sift through enormous data points to find information that is most useful during a given event. The chapter also presents our ongoing IT-system that processes and analyses social media data to transform the excessive volume of low information content into small volume but rich content that is useful to emergency personnel.
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2. Big Data And Emergency Cycle

Big data is the technological paradigm that enables useful analysis of vast quantities of data to be achieved in practice. Big data is the collection of scientific and engineering methods and tools for dealing with such volumes of data, and addresses not merely the storage but also access to and distribution, analysis, and useful presentation of results (such as visualisation of analysis of the data) for huge volumes of data. Big data is becoming a critical part of emergency communication. Emergency communication does not involve only intentional, explicit exchange of messages – for example first responders talking over a voice connection, or an announcement of a text message warning to citizens threatened by an approaching natural disaster. To be more precise, emergency communication also involves the monitoring and understanding of the complete body of public, openly available communication – such as messages and content being publicly exchanged on social media. Thus, individuals may be reporting their condition to loved ones or making specific requests for help, but a complete analysis of all communications can reveal valuable information of general scope, such as a disease outbreak.1

Usually, emergency cycle consists of three phases. “Prevention” and “Preparedness” are conducted before an emergency occurs in order to eliminate or reduce the probability of an emergency and to build emergency management capacities. “Response” activities provide emergency assistance to save lives, preserve property and protect the environment during an emergency. “Recovery” is the process of returning systems to normal levels after an emergency. Big data has been used in all phases of the emergency management cycle as shown in the following Table 1.

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